Guang-Ze Yang
Researcher in Control Theory & Robotics
Also Known As
Grayson Young
楊 広沢 (よう こうたく)
杨 广泽 (Yang Guang-Ze)
About Me
I build optimal, safety-critical controllers for multi-robot systems. At Ibaraki University (Japan), my research focuses on enabling teams of robots to collaborate effectively through distributed and robust optimal control strategies in real-time. Through my Notebook, I share knowledge and insights on robotics, control theory, programming, and personal growth.
Current Focus
- Research: Model Predictive Control (MPC), Control Barrier Functions (CBF)
- Status: Starting full-time career in autonomous multi-robot systems research, April 2026
- Building: Open-source projects related to MPC, CBF and formation control
- Learning: Publishing for academic journals
Research Interests
- Optimal & Robust Control
Applying advanced control theory to ensure system performance and stability under disturbances and model uncertainties. - Distributed Multi-Robot Control
Designing decentralized algorithms that enable robot teams to perform complex tasks collaboratively. - Motion Control & Path Planning
Developing algorithms for autonomous robot navigation and obstacle avoidance.
Education
Master of Engineering
Mechanical Systems Engineering
Ibaraki University
April 2024 – March 2026Bachelor of Engineering
Mechanical Systems Engineering
Ibaraki University
April 2020 – March 2024Publications
Safety-Critical Formation Tracking Control of Multi-Robot Systems via CLF-CBF-QP
2025 International Conference on Advanced Mechatronic Systems (ICAMechS)
This paper proposes a novel Hierarchical Fallback CLF-CBF-QP framework for safety-critical formation tracking. The approach employs CLF for tracking and High-Order CBFs for safety, featuring a three-stage fallback strategy that resolves QP infeasibility by prioritizing safety over performance while maintaining computational efficiency.
Distributed Robust Time-Varying Formation Control of Multi-Agent Systems Under Disturbances
2024 SICE Festival with Annual Conference (SICE FES)
This work considers the problem of time-varying formation tracking control of second-order multi-agent systems under disturbances. A distributed robust time-varying formation control law is proposed including distributed finite-time estimators of the leader states and sliding mode time-varying formation controllers.
Technical Skills
Foundational Knowledge
Mathematical Analysis
- Linear & Matrix Algebra
- Calculus & Differential Equations
- Complex & Frequency Analysis
- Probability & Statistics
Applying Mathematics
- Optimization (Convex & NLP)
- Graph Theory
- Algorithm & Data Structure
- Numerical Analysis
ME Fundamentals
- Theoretical Mechanics
- Mechanics of Materials
- Fluid Mechanics
- Thermodynamics
EE Fundamentals
- Electrical Circuits & Systems
- Analog & Digital Circuits
- Mechatronics
Core Research Domains
Control Theory
- Optimal & Robust Control
- Nonlinear Control
- Distributed Multi-Robot Systems
- Model Predictive Control (MPC)
Robotics
- Kinematics & Dynamics
- Motion Control & Path Planning
- Mobile Robotics
- Computer Vision
Artificial Intelligence
- Machine Learning (ML)
- Reinforcement Learning (RL)
- Neural Networks (NNs)
Programming Languages
MATLAB
Algorithm Prototyping
Control System Simulation
Python
AI/ML Development
Data Analysis
C / C++
Real-time Systems
Embedded Systems
Web Tech
JavaScript, HTML, CSS
(Data Visualization)
Development Environment
Development Tools
Frameworks & Libraries
Operating Systems
Microcontrollers (MCUs)
- Raspberry Pi, Arduino, STM32, H8
Languages
Chinese
English
Japanese
Personal Interests
- Fitness
Training & running 4×/week - Sports
Weekly basketball sessions - Reading
Biography, Philosophy, Self-improvement
- Gaming
Zelda, Fire Emblem, Monster Hunter - Music
J-pop, R&B
Philosophy
"Stoic in hardship, humble in success."
"知之者不如好之者，好之者不如樂之者。" — Confucius
This philosophy forms the cornerstone of my approach to both research and life. I believe that pursuing meaningful work demands the perseverance to face challenging, long-term problems, as well as the humility to continuously learn from new insights and to collaborate openly and effectively with others.
Let's Connect!
I'm always open to discussing research opportunities, collaboration, or connecting with fellow enthusiasts in robotics and control systems.